With the rapid development of the Internet of Vehicles (IoV), computationally intensive and latency-sensitive applications are emerging at an increasing pace. Traditional resource allocation and task scheduling methods are no longer sufficient to meet the demands for efficiency and reliability. Recently, semantic communication has gained attention as an efficient communication paradigm that reduces transmission bandwidth requirements by conveying the actual meaning of data rather than information bits. This chapter proposes a semantic communication-based task offloading and resource allocation scheme for IoV systems with multiple vehicles and heterogeneous tasks. By integrating semantic information such as task urgency and importance, the scheme jointly optimizes task offloading and computational resource allocation to improve system performance. A cost function is formulated considering factors such as semantic accuracy, relative delay, reward for task importance, and the social contribution rate. The simulation results demonstrate that the proposed scheme significantly improves the overall utility of the system compared to traditional algorithms.